Yeast Platforms for Production and Screening of Bioactive Derivatives of Rauwolscine

Monoterpene indole alkaloids (MIAs) make up a highly bioactive class of metabolites produced by a range of tropical and subtropical plants. The corynanthe-type MIAs are a stereochemically complex subclass with therapeutic potential against a large number of indications including cancer, psychotic disorders, and erectile dysfunction. Here, we report yeast-based cell factories capable of de novo production of corynanthe-type MIAs rauwolscine, yohimbine, tetrahydroalstonine, and corynanthine. From this, we demonstrate regioselective biosynthesis of 4 fluorinated derivatives of these compounds and de novo biosynthesis of 7-chlororauwolscine by coexpression of a halogenase with the biosynthetic pathway. Finally, we capitalize on the ability of these cell factories to produce derivatives of these bioactive scaffolds to establish a proof-of-principle drug discovery pipeline in which the corynanthe-type MIAs are screened for bioactivity on human drug targets, expressed in yeast. In doing so, we identify antagonistic and agonistic behavior against the human adrenergic G protein-coupled receptors ADRA2A and ADRA2B, and the serotonergic receptor 5HT4b, respectively. This study thus demonstrates a proto-drug discovery pipeline for bioactive plant-inspired small molecules based on one-pot biocatalysis of natural and new-to-nature corynanthe-type MIAs in yeast.

Genome-wide host-pathway interactions affecting cis-cis-muconic acid production in yeast

The success of forward metabolic engineering depends on a thorough understanding of the behaviour of a heterologous metabolic pathway within its host. We have recently described CRI-SPA, a high-throughput gene editing method enabling the delivery of a metabolic pathway to all strains of the Saccharomyces cerevisiae knock-out library. CRI-SPA systematically quantifies the effect of each modified gene present in the library on product synthesis, providing a complete map of host:pathway interactions. In its first version, CRI-SPA relied on the colour of the product betaxanthins to quantify strains synthesis ability. However, only a few compounds produce a visible or fluorescent phenotype limiting the scope of our approach. Here, we adapt CRI-SPA to onboard a biosensor reporting the interactions between host genes and the synthesis of the colourless product cis-cis-muconic acid (CCM). We phenotype >9,000 genotypes, including both gene knock-out and overexpression, by quantifying the fluorescence of yeast colonies growing in high-density agar arrays. We identify novel metabolic targets belonging to a broad range of cellular functions and confirm their positive impact on CCM biosynthesis. In particular, our data suggests a new interplay between CCM biosynthesis and cytosolic redox through their common interaction with the oxidative pentose phosphate pathway. Our genome-wide exploration of host:pathway interaction opens novel strategies for improved production of CCM in yeast cell factories.

Combining enzyme and metabolic engineering for microbial supply of therapeutic phytochemicals

The history of pharmacology is deeply intertwined with plant-derived compounds, which continue to be crucial in drug development. However, their complex structures and limited availability in plants challenge drug discovery, optimization, development, and industrial production via chemical synthesis or natural extraction. This review delves into the integration of metabolic and enzyme engineering to leverage micro-organisms as platforms for the sustainable and reliable production of therapeutic phytochemicals. We argue that engineered microbes can serve a triple role in this paradigm: facilitating pathway discovery, acting as cell factories for scalable manufacturing, and functioning as platforms for chemical derivatization. Analyzing recent progress and outlining future directions, the review highlights microbial biotechnology's transformative potential in expanding plant-derived human therapeutics' discovery and supply chains.

Codon-tRNA Coadaptation Bias for Identifying Strong Native Promoters in Komagataella phaffii

Promoters are crucial elements for engineering microbial production strains used in bioprocesses. For the increasingly popular chassis Komagataella phaffii (formerly Pichia pastoris), a limited number of well-characterized promoters constrain the data-driven engineering of production strains. Here, we present an in silico approach for condition-independent de novo identification of strong native promoters. The method relies on tRNA-codon coadaptation of coding sequences in the K. phaffii genome and is based on two complementary scores: the number of effective codons and the tRNA adaptation index. Genes with high codon bias are expected to be translated efficiently and, thus, also be under control of strong promoters. Using this approach, we identified promising strong promoter candidates and experimentally assessed their activity using fluorescent reporter assays characterizing 50 promoters spanning a 76-fold difference in expression levels in a glucose medium. Overall, we report several promoters that should be added to the molecular toolbox for engineering of K. phaffii and present an approach for identifying promoters in microbial genomes.

Can biotechnology lead the way toward a sustainable pharmaceutical industry?

The impact-intensive and rapidly growing pharmaceutical industry must ensure its sustainability. This study reveals that environmental sustainability assessments have been conducted for only around 0.2% of pharmaceuticals, environmental impacts have significant variations among the assessed products, and different impact categories have not been consistently studied. Highly varied impacts require assessing more products to understand the industry's sustainability status. Reporting all impact categories will be crucial, especially when comparing production technologies. Biological production of (semi)synthetic pharmaceuticals could reduce their environmental costs, though the high impacts of biologically produced monoclonal antibodies should also be optimized. Considering the sustainability potential of biopharmaceuticals from economic, environmental, and social perspectives, collaboratively guiding their immense market growth would lead to the industry's sustainability transition.

teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.

Biosynthesis of natural and halogenated plant monoterpene indole alkaloids in yeast

Monoterpenoid indole alkaloids (MIAs) represent a large class of plant natural products with marketed pharmaceutical activities against a wide range of indications, including cancer, malaria and hypertension. Halogenated MIAs have shown improved pharmaceutical properties; however, synthesis of new-to-nature halogenated MIAs remains a challenge. Here we demonstrate a platform for de novo biosynthesis of two MIAs, serpentine and alstonine, in baker's yeast Saccharomyces cerevisiae and deploy it to systematically explore the biocatalytic potential of refactored MIA pathways for the production of halogenated MIAs. From this, we demonstrate conversion of individual haloindole derivatives to a total of 19 different new-to-nature haloserpentine and haloalstonine analogs. Furthermore, by process optimization and heterologous expression of a modified halogenase in the microbial MIA platform, we document de novo halogenation and biosynthesis of chloroalstonine. Together, this study highlights a microbial platform for enzymatic exploration and production of complex natural and new-to-nature MIAs with therapeutic potential.

HSP70-binding motifs function as protein quality control degrons

Protein quality control (PQC) degrons are short protein segments that target misfolded proteins for proteasomal degradation, and thus protect cells against the accumulation of potentially toxic non-native proteins. Studies have shown that PQC degrons are hydrophobic and rarely contain negatively charged residues, features which are shared with chaperone-binding regions. Here we explore the notion that chaperone-binding regions may function as PQC degrons. When directly tested, we found that a canonical Hsp70-binding motif (the APPY peptide) functioned as a dose-dependent PQC degron both in yeast and in human cells. In yeast, Hsp70, Hsp110, Fes1, and the E3 Ubr1 target the APPY degron. Screening revealed that the sequence space within the chaperone-binding region of APPY that is compatible with degron function is vast. We find that the number of exposed Hsp70-binding sites in the yeast proteome correlates with a reduced protein abundance and half-life. Our results suggest that when protein folding fails, chaperone-binding sites may operate as PQC degrons, and that the sequence properties leading to PQC-linked degradation therefore overlap with those of chaperone binding.

Engineered cell differentiation and sexual reproduction in probiotic and mating yeasts

G protein-coupled receptors (GPCRs) enable cells to sense environmental cues and are indispensable for coordinating vital processes including quorum sensing, proliferation, and sexual reproduction. GPCRs comprise the largest class of cell surface receptors in eukaryotes, and for more than three decades the pheromone-induced mating pathway in baker's yeast Saccharomyces cerevisiae has served as a model for studying heterologous GPCRs (hGPCRs). Here we report transcriptome profiles following mating pathway activation in native and hGPCR-signaling yeast and use a model-guided approach to correlate gene expression to morphological changes. From this we demonstrate mating between haploid cells armed with hGPCRs and endogenous biosynthesis of their cognate ligands. Furthermore, we devise a ligand-free screening strategy for hGPCR compatibility with the yeast mating pathway and enable hGPCR-signaling in the probiotic yeast Saccharomyces boulardii. Combined, our findings enable new means to study mating, hGPCR-signaling, and cell-cell communication in a model eukaryote and yeast probiotics.

Metoprolol improves left ventricular longitudinal function at rest and during exercise in obstructive hypertrophic cardiomyopathy

Background

Hypertrophic cardiomyopathy (HCM) patients with outflow obstruction often experience symptoms of heart failure upon exertion. We aimed to characterize left ventricular (LV) systolic function by segmental and global longitudinal strain echocardiography, and to investigate changes in relation to exercise, and the effect of standard treatment with beta-blockers.

Method

Twenty-nine patients with obstructive HCM and New York Heart Association (NYHA) class ≥ II symptoms were enrolled in a double-blind, placebo-controlled, randomized crossover trial. Patients received metoprolol 150 mg or placebo for two consecutive two-week periods in random order. Echocardiographic assessment with speckle-tracking derived longitudinal strain (LS) was performed at rest and during peak exercise at the end of each treatment period. Segmental LS was calculated as the mean of the six apical, mid, and basal segments.

Results

During placebo treatment resting values of segmental LS showed an apical-basal difference of −10.3% (95% confidence interval (CI): −12.7 to −7.8; p<0.0001), with severely depressed values of the basal segment −9.3 (4.2) %. Treatment with metoprolol improved LS of the apical segment (−2.8%; 95% CI: −4.2 to −1.3; p<0.001) and mid segment (−1.1%; 95% CI: −2.0 to −0.3; p=0.007). The segmental improvement with metoprolol treatment was reflected in an increase in resting global LS (LV GLS) (−1.4%; 95% CI: −2.3 to −0.6; p<0.001). Peak exercise was associated with a reduction in LV GLS, yet the improvement in LV GLS during metoprolol was consistent upon exercise (−1.3%; 95% CI: −2.6 to −0.1; p=0.03).

Conclusion

Segmental LS of the LV in obstructive HCM showed an abnormal apical-basal difference. Exercise was associated with a reduction in LV GLS, illustrating an impaired myocardial functional reserve capacity. Metoprolol significantly improved LS of the apical and mid segments of the LV at rest and LV GLS during exercise.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Novo nordic foundation

Temporal trends, characteristics and comorbidities of patients with hypertrophic cardiomyopathy in Denmark from 2005 to 2018: a nationwide cohort study

Background

The majority of patients with Hypertrophic cardiomyopathy (HCM) are mildly symptomatic or unaware of their condition, but some develop serious complications such as heart failure, atrial fibrillation (AF) as well as sudden cardiac death. Previous studies have suggested that HCM detection-rates in women are significantly lower than in men. This leads to diagnosis often being delayed to later stages of the disease in women, where symptoms are more severe. Further characterization of HCM patients to improve early detection of adverse outcomes and warning signs might improve long-term outcomes.

Purpose

To describe the characteristics of Danish patients diagnosed with HCM between 2005–2018 and determine trends and changes in these factors over time.

Methods

All patients aged 16 years or older with a diagnosis of HCM between the 1st of January 2005 and the 31st of December 2018 were identified in Danish nationwide administrative registers and included in the study.

Time trends were calculated, and differences analyzed using the Cochran-Armitage trend test and linear regression.

Results

A total of 3856 patients were diagnosed with HCM in the study period and included in the study. The median age at diagnosis was 68 years (IQR 56 and 78 years), 53% were male, and 44% were diagnosed with obstructive HCM, while the number of patients diagnosed with HCM each year overall increased. At the time of diagnosis, 22,3% patients were previously diagnosed with ischemic heart disease, 17% with AF, 7,5% with ischemic stroke, 13,6% with heart failure. Median age and gender distribution remained stable over time, while the proportion of obstructive HCM among the newly diagnosed decreased (p = <0.001) (Figure1). During the study period, there was a significant decrease in the prevalence of heart failure (p = <0.001), ischemic heart disease (p = <0.001), and chronic obstructive pulmonary syndrome (p = <0.001), while the prevalence of AF, hypertension and ischemic stroke remained stable (Figure 2).

Conclusion

Despite previous studies describing a gender gap in patients diagnosed with HCM, gender distribution was near equal in this cohort. The number of patients diagnosed with non-obstructive HCM is increasing and the prevalence of comorbidities such as heart failure, ischemic heart disease, and COPD decreased over time.

Whether these findings are the result of improved early detection of HCM warrants further research and examination.

Funding Acknowledgement

Type of funding sources: Public hospital(s). Main funding source(s): Herlev-Gentofte Hospital, Denmark

Serotonin G Protein-Coupled Receptor-Based Biosensing Modalities in Yeast

Serotonin is a key neurotransmitter involved in numerous physiological processes and serves as an important precursor for manufacturing bioactive indoleamines and alkaloids used in the treatment of human pathologies. In humans, serotonin sensing and signaling can occur by 12 G protein-coupled receptors (GPCRs) coupled to Gα proteins. In yeast, human serotonin GPCRs coupled to Gα proteins have previously been shown to function as whole-cell biosensors of serotonin. However, systematic characterization of serotonin biosensing modalities between variant serotonin GPCRs and application thereof for high-resolution serotonin quantification is still awaiting. To systematically assess GPCR signaling in response to serotonin, we characterized reporter gene expression at two different pHs of a 144-sized library encoding all 12 human serotonin GPCRs in combination with 12 different Gα proteins engineered in yeast. From this screen, we observed changes in the biosensor sensitivities of >4 orders of magnitude. Furthermore, adopting optimal biosensing designs and pH conditions enabled high-resolution high-performance liquid chromatography-validated sensing of serotonin produced in yeast. Lastly, we used the yeast platform to characterize 19 serotonin GPCR polymorphisms found in human populations. While major differences in signaling were observed among the individual polymorphisms when studied in yeast, a cross-comparison of selected variants in mammalian cells showed both similar and disparate results. Taken together, our study highlights serotonin biosensing modalities of relevance to both biotechnological and potential human health applications.

Atrial fibrillation and stroke risk of patients with hypertrophic cardiomyopathy in denmark from 2005-2018: a nationwide cohort study

Funding Acknowledgements

Type of funding sources: Public hospital(s). Main funding source(s): Internal funding: Herlev-Gentofte Cardiovascular Research Department.

Background

Hypertrophic cardiomyopathy (HCM) can be associated with serious complications such as heart failure, atrial fibrillation (AF) and sudden cardiac death. The treatment of AF in HCM patients can be challenging since AF often aggravates symptoms. Previous studies have suggested that HCM patients with AF have an elevated risk of thromboembolism and stroke compared to AF patients without HCM regardless of their CHA2DS2VASc score.

Purpose

To determine the risk of AF and stroke in HCM patients.

Methods

Through the Danish National Registers all patients aged 16 or older diagnosed with HCM between the 1st of January 2005, and the 31st of December 2018 were included in the analysis. The association between HCM, AF, and stroke was investigated using multivariable Cox proportional-hazard analysis adjusted for gender, age, atrial fibrillation, ischemic heart disease, chronic obstructive pulmonary disease, chronic kidney disease and hypertension. Cumulative incidence of AF and stroke was calculated using the Aalen-Johansen estimator, taking death as a competing risk into account.

Results

A total of 3856 patients were included, 2060 (53,4%) were male and median age of 67,8 (IQR 56 and 77,8) years. During the study period, 384 (10%) patients were diagnosed with AF. The risk of AF was significantly lower in males (HR 0,72 (0,59–0,90), p-value = 0.003) and for patients below 60 years (HR 0,18 (0,12–0,27), p-value = <0.001). (Figure 1)

157 (4,1%) of the HCM patients developed stroke. The risk of developing stroke was significantly decreased for patients aged under 60 (HR 0,32 (0,2–0,52), p-value = <0.001). There was no increased risk of stroke comparing genders.

Stroke risk was further analyzed in patients with known AF at time of inclusion, 656 (17%) in total. Compared to patients without AF and adjusted for age, gender and co-morbidities, there was no significant difference in stroke risk between these groups (HR 1.2 (0,81-1,76), p-value = 0.36). (Figure 2)

Conclusion

AF and stroke are common complications in HCM. Women are more susceptible to developing AF than men, and age over 60 at the time of diagnosis was associated with significantly higher risk of AF and stroke. HCM patients with previously known AF did not have a significantly elevated risk of stroke. More research will be needed to further explore these connections.

RNA-mediated in vivo Directed Evolution in Yeast

Directed evolution is a powerful approach to obtain genetically-encoded sought-for traits. Compared to the prolonged adaptation regimes to mutations occurring under natural selection, directed evolution unlocks rapid screening and selection of mutants with improved traits from vast mutated sequence spaces. Many systems have been developed to search variant landscapes based on ex vivo or in vivo mutagenesis, to identify and select new-to-nature and optimized properties in biomolecules. Yet, the majority of such systems rely on tedious iterations of library preparation, propagation, and selection steps. Furthermore, among the relatively few in vivo directed evolution systems developed to mitigate handling of repetitive ex vivo steps, directed evolution of DNA is the standard approach. Here, we present the protocol for designing the transfer of genetic information from evolving RNA donors to DNA in baker's yeast, using CRISPR- and RNA-assisted in vivo directed evolution (CRAIDE). We use mutant T7 RNA polymerase to introduce mutations in RNA donors, while incorporation into DNA is directed by CRISPR/Cas9. As such, CRAIDE offers an opportunity to study fundamental questions, such as RNA's contribution to the evolution of DNA-based life on Earth. Graphic abstract: CRISPR- and RNA-assisted in vivo directed evolution (CRAIDE).

CasPER: A CRISPR/Cas9-Based Method for Directed Evolution in Genomic Loci in Saccharomyces cerevisiae

Here, in this chapter, we describe a detailed protocol for the method named Cas9-mediated protein evolution reaction or short CasPER. CasPER is based on the generation of large 300-600-bp mutagenized linear DNA fragments by error-prone PCR which are used as a donor for repair of double-strand break mediated by Cas9 and subsequently integrated to the genome. This method can be efficiently used for directed evolution of desired essential or nonessential genes in the genome and most importantly can be multiplexed. Altogether, the described method allows for heterogeneous DNA integration with successful transformation efficiencies of 98-100% for both single and multiplex targeting.

Integrating continuous hypermutation with high-throughput screening for optimization of cis,cis-muconic acid production in yeast

Directed evolution is a powerful method to optimize proteins and metabolic reactions towards user-defined goals. It usually involves subjecting genes or pathways to iterative rounds of mutagenesis, selection and amplification. While powerful, systematic searches through large sequence-spaces is a labour-intensive task, and can be further limited by a priori knowledge about the optimal initial search space, and/or limits in terms of screening throughput. Here, we demonstrate an integrated directed evolution workflow for metabolic pathway enzymes that continuously generate enzyme variants using the recently developed orthogonal replication system, OrthoRep and screens for optimal performance in high-throughput using a transcription factor-based biosensor. We demonstrate the strengths of this workflow by evolving a rate-limiting enzymatic reaction of the biosynthetic pathway for cis,cis-muconic acid (CCM), a precursor used for bioplastic and coatings, in Saccharomyces cerevisiae. After two weeks of simply iterating between passaging of cells to generate variant enzymes via OrthoRep and high-throughput sorting of best-performing variants using a transcription factor-based biosensor for CCM, we ultimately identified variant enzymes improving CCM titers > 13-fold compared with reference enzymes. Taken together, the combination of synthetic biology tools as adopted in this study is an efficient approach to debottleneck repetitive workflows associated with directed evolution of metabolic enzymes.

Clinical effects of metoprolol in obstructive hypertrophic cardiomyopathy (TEMPO). A randomized, double-blinded, placebo-controlled crossover trial

Background

Treatment with beta blockers (BB) has been used for symptomatic relief in patients with obstructive hypertrophic cardiomyopathy (HCM) for decades. Even so, the guideline recommendation for the use of BB rests on expert opinions and observational cohort studies. Providing comprehensive high-quality data on the effects of BB in obstructive HCM is essential, especially in the context of newly developed pharmacological treatment strategies specifically targeting this disease (1).

Purpose

The study aimed to investigate the effects of metoprolol on left ventricular outflow tract (LVOT) obstruction, symptoms, and exercise capacity in patients with obstructive HCM.

Methods

This double-blinded, placebo-controlled, randomized crossover trial enrolled 30 patients with obstructive HCM and New York Heart Association (NYHA) class ≥ II symptoms from 1 May 2018 to 1 September 2020. Patients received metoprolol or placebo for two consecutive two-week periods in random order. The effect parameters were LVOT gradients, NYHA class, Canadian Cardiovascular Society (CCS) grading angina class, Kansas City Cardiomyopathy Questionnaire Overall Summary Score (KCCQ-OSS), and cardiopulmonary exercise testing.

Results

Compared with placebo, the LVOT gradient during metoprolol was lower at rest (25 [15–58] mmHg versus 72 [28–87] mmHg; p=0.007), at peak exercise (28 [18–40] mmHg versus 62 [31–113] mmHg; p<0.001), and post-exercise (45 [24–100] mmHg versus 115 [55–171] mmHg; p<0.0001) (figure 1). During metoprolol treatment, 14% of patients were in NYHA class III compared with 38% on placebo (p<0.01). Likewise, no patients were in CCS class ≥ III during metoprolol compared with 10% during placebo (p<0.01). These findings were confirmed by a higher KCCQ-OSS score during metoprolol (76.2 (16.2) versus 73.8 (19.5), p=0.039) (figure 2). Peak oxygen consumption did not differ between study arms.

Conclusion

Compared with placebo, metoprolol reduced LVOT obstruction at rest and during exercise, provided symptom relief, and improved quality of life in patients with obstructive HCM. However, exercise capacity remained unchanged. Findings from the present study support the guideline recommendations that BB should be the first drug of choice in patients with obstructive HCM who develop symptoms.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Novo nordic foundation, Skibsreder Per Henriksen, R. og hustrus Foundation

Metabolic engineering for plant natural products biosynthesis: new procedures, concrete achievements and remaining limits

Microorganisms and plants represent major sources of natural compounds with a plethora of bioactive properties. Among these, plant natural products (PNPs) remain indispensable to human health. With few exceptions, PNP-based pharmaceuticals come from plant specialized metabolisms and display a structure far too complex for a profitable production by total chemical synthesis. Accordingly, their industrial processes of supply are still mostly based on the extraction of final products or precursors directly from plant materials. This implies that particular contexts (e.g. pandemics, climate changes) and natural resource overexploitation are main drivers for the high production cost and recurrent supply shortages. Recently, biotechnological manufacturing alternatives gave rise to a multitude of benchmark studies implementing the production of important PNPs in various heterologous hosts. Here, we spotlight unprecedented advancements in the field of metabolic engineering dedicated to the heterologous production of a prominent series of PNPs that were achieved during the year 2020. We also discuss how the knowledge accumulated in recent years could pave the way for a broader manufacturing palette of natural products from a wide range of natural resources.

Engineering G protein-coupled receptor signalling in yeast for biotechnological and medical purposes

G protein-coupled receptors (GPCRs) comprise the largest class of membrane proteins in the human genome, with a common denominator of seven-transmembrane domains largely conserved among eukaryotes. Yeast is naturally armoured with three different GPCRs for pheromone and sugar sensing, with the pheromone pathway being extensively hijacked for characterising heterologous GPCR signalling in a model eukaryote. This review focusses on functional GPCR studies performed in yeast and on the elucidated hotspots for engineering, and discusses both endogenous and heterologous GPCR signalling. Key emphasis will be devoted to studies describing important engineering parameters to consider for successful coupling of GPCRs to the yeast mating pathway. We also review the various means of applying yeast for studying GPCRs, including the use of yeast armed with heterologous GPCRs as a platform for (i) deorphanisation of orphan receptors, (ii) metabolic engineering of yeast for production of bioactive products and (iii) medical applications related to pathogen detection and drug discovery. Finally, this review summarises the current challenges related to expression of functional membrane-bound GPCRs in yeast and discusses the opportunities to continue capitalising on yeast as a model chassis for functional GPCR signalling studies.

A Reporter System for Cytosolic Protein Aggregates in Yeast

Protein misfolding and aggregation are linked to neurodegenerative diseases of mammals and suboptimal protein expression within biotechnology. Tools for monitoring protein aggregates are therefore useful for studying disease-related aggregation and for improving soluble protein expression in heterologous hosts for biotechnology purposes. In this work, we developed a promoter-reporter system for aggregated protein on the basis of the yeast native response to misfolded protein. To this end, we first studied the proteome of yeast in response to the expression of folded soluble and aggregation-prone protein baits and identified genes encoding proteins related to protein folding and the response to heat stress as well as the ubiquitin-proteasome system that are over-represented in cells expressing an aggregation-prone protein. From these data, we created and validated promoter-reporter constructs and further engineered the best performing promoters by increasing the copy number of upstream activating sequences and optimization of culture conditions. Our best promoter-reporter has an output dynamic range of approximately 12-fold upon expression of the aggregation-prone protein and responded to increasing levels of aggregated protein. Finally, we demonstrate that the system can discriminate between yeast cells expressing different prion precursor proteins and select the cells expressing folded soluble protein from mixed populations. Our reporter system is thus a simple tool for diagnosing protein aggregates in living cells and should be applicable for the health and biotechnology industries.

Dietary Change Enables Robust Growth-Coupling of Heterologous Methyltransferase Activity in Yeast

Genetic modifications of living organisms and proteins are made possible by a catalogue of molecular and synthetic biology tools, yet proper screening assays for genetic variants of interest continue to lag behind. Synthetic growth-coupling (GC) of enzyme activities offers a simple, inexpensive way to track such improvements. In this follow-up study we present the optimization of a recently established GC design for screening of heterologous methyltransferases (MTases) and related pathways in the yeast Saccharomyces cerevisiae. Specifically, upon testing different media compositions and genetic backgrounds, improved GC of different heterologous MTase activities is obtained. Furthermore, we demonstrate the strength of the system by screening a library of catechol O-MTase variants converting protocatechuic acid into vanillic acid. We demonstrated high correlation (R² = 0.775) between vanillic acid and cell density as a proxy for MTase activity. We envision that the improved MTase GC can aid evolution-guided optimization of biobased production processes for methylated compounds with yeast in the future.

Deploying Microbial Synthesis for Halogenating and Diversifying Medicinal Alkaloid Scaffolds

Plants produce some of the most potent therapeutics and have been used for thousands of years to treat human diseases. Today, many medicinal natural products are still extracted from source plants at scale as their complexity precludes total synthesis from bulk chemicals. However, extraction from plants can be an unreliable and low-yielding source for human therapeutics, making the supply chain for some of these life-saving medicines expensive and unstable. There has therefore been significant interest in refactoring these plant pathways in genetically tractable microbes, which grow more reliably and where the plant pathways can be more easily engineered to improve the titer, rate and yield of medicinal natural products. In addition, refactoring plant biosynthetic pathways in microbes also offers the possibility to explore new-to-nature chemistry more systematically, and thereby help expand the chemical space that can be probed for drugs as well as enable the study of pharmacological properties of such new-to-nature chemistry. This perspective will review the recent progress toward heterologous production of plant medicinal alkaloids in microbial systems. In particular, we focus on the refactoring of halogenated alkaloids in yeast, which has created an unprecedented opportunity for biosynthesis of previously inaccessible new-to-nature variants of the natural alkaloid scaffolds.

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be combined to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets, efficient library construction of metabolic pathway designs, and high-throughput biosensor-enabled screening for training diverse machine learning algorithms. From a single data-generation cycle, this enables successful forward engineering of complex aromatic amino acid metabolism in yeast, with the best machine learning-guided design recommendations improving tryptophan titer and productivity by up to 74 and 43%, respectively, compared to the best designs used for algorithm training. Thus, this study highlights the power of combining mechanistic and machine learning models to effectively direct metabolic engineering efforts.

Improvement of cis,cis-Muconic Acid Production in Saccharomyces cerevisiae through Biosensor-Aided Genome Engineering

Muconic acid is a potential platform chemical for the production of nylon, polyurethanes, and terephthalic acid. It is also an attractive functional copolymer in plastics due to its two double bonds. At this time, no economically viable process for the production of muconic acid exists. To harness novel genetic targets for improved production of cis,cis-muconic acid (CCM) in the yeast Saccharomyces cerevisiae, we employed a CCM-biosensor coupled to GFP expression with a broad dynamic response to screen UV-mutagenesis libraries of CCM-producing yeast. Via fluorescence activated cell sorting we identified a clone Mut131 with a 49.7% higher CCM titer and 164% higher titer of biosynthetic intermediate-protocatechuic acid (PCA). Genome resequencing of the Mut131 and reverse engineering identified seven causal missense mutations of the native genes (PWP2, EST2, ATG1, DIT1, CDC15, CTS2, and MNE1) and a duplication of two CCM biosynthetic genes, encoding dehydroshikimate dehydratase and catechol 1,2-dioxygenase, which were not recognized as flux controlling before. The Mut131 strain was further rationally engineered by overexpression of the genes encoding for PCA decarboxylase and AROM protein without shikimate dehydrogenase domain (Aro1p^ΔE), and by restoring URA3 prototrophy. The resulting engineered strain produced 20.8 g/L CCM in controlled fed-batch fermentation, with a yield of 66.2 mg/g glucose and a productivity of 139 mg/L/h, representing the highest reported performance metrics in a yeast for de novo CCM production to date and the highest production of an aromatic compound in yeast. The study illustrates the benefit of biosensor-based selection and brings closer the prospect of biobased muconic acid.

Evolution-guided engineering of small-molecule biosensors

Allosteric transcription factors (aTFs) have proven widely applicable for biotechnology and synthetic biology as ligand-specific biosensors enabling real-time monitoring, selection and regulation of cellular metabolism. However, both the biosensor specificity and the correlation between ligand concentration and biosensor output signal, also known as the transfer function, often needs to be optimized before meeting application needs. Here, we present a versatile and high-throughput method to evolve prokaryotic aTF specificity and transfer functions in a eukaryote chassis, namely baker's yeast Saccharomyces cerevisiae. From a single round of mutagenesis of the effector-binding domain (EBD) coupled with various toggled selection regimes, we robustly select aTF variants of the cis,cis-muconic acid-inducible transcription factor BenM evolved for change in ligand specificity, increased dynamic output range, shifts in operational range, and a complete inversion-of-function from activation to repression. Importantly, by targeting only the EBD, the evolved biosensors display DNA-binding affinities similar to BenM, and are functional when ported back into a prokaryotic chassis. The developed platform technology thus leverages aTF evolvability for the development of new host-agnostic biosensors with user-defined small-molecule specificities and transfer functions.

High-Resolution Scanning of Optimal Biosensor Reporter Promoters in Yeast

Small-molecule binding allosteric transcription factors (aTFs) derived from bacteria enable real-time monitoring of metabolite abundances, high-throughput screening of genetic designs, and dynamic control of metabolism. Yet, engineering of reporter promoter designs of prokaryotic aTF biosensors in eukaryotic cells is complex. Here we investigate the impact of aTF binding site positions at single-nucleotide resolution in >300 reporter promoter designs in Saccharomyces cerevisiae. From this we identify biosensor output landscapes with transient and distinct aTF binding site position effects for aTF repressors and activators, respectively. Next, we present positions for tunable reporter promoter outputs enabling metabolite-responsive designs for a total of four repressor-type and three activator-type aTF biosensors with dynamic output ranges up to 8- and 26-fold, respectively. This study highlights aTF binding site positions in reporter promoters as key for successful biosensor engineering and that repressor-type aTF biosensors allows for more flexibility in terms of choice of binding site positioning compared to activator-type aTF biosensors.

Programmable polyketide biosynthesis platform for production of aromatic compounds in yeast

To accelerate the shift to bio-based production and overcome complicated functional implementation of natural and artificial biosynthetic pathways to industry relevant organisms, development of new, versatile, bio-based production platforms is required. Here we present a novel yeast-based platform for biosynthesis of bacterial aromatic polyketides. The platform is based on a synthetic polyketide synthase system enabling a first demonstration of bacterial aromatic polyketide biosynthesis in a eukaryotic host.

Modular 5'-UTR hexamers for context-independent tuning of protein expression in eukaryotes

Functional characterization of regulatory DNA elements in broad genetic contexts is a prerequisite for forward engineering of biological systems. Translation initiation site (TIS) sequences are attractive to use for regulating gene activity and metabolic pathway fluxes because the genetic changes are minimal. However, limited knowledge is available on tuning gene outputs by varying TISs in different genetic and environmental contexts. Here, we created TIS hexamer libraries in baker’s yeast Saccharomyces cerevisiae directly 5′ end of a reporter gene in various promoter contexts and measured gene activity distributions for each library. Next, selected TIS sequences, resulted in almost 10-fold changes in reporter outputs, were experimentally characterized in various environmental and genetic contexts in both yeast and mammalian cells. From our analyses, we observed strong linear correlations (R² = 0.75–0.98) between all pairwise combinations of TIS order and gene activity. Finally, our analysis enabled the identification of a TIS with almost 50% stronger output than a commonly used TIS for protein expression in mammalian cells, and selected TISs were also used to tune gene activities in yeast at a metabolic branch point in order to prototype fitness and carotenoid production landscapes. Taken together, the characterized TISs support reliable context-independent forward engineering of translation initiation in eukaryotes.

Engineered Reversal of Function in Glycolytic Yeast Promoters

Promoters are key components of cell factory design, allowing precise expression of genes in a heterologous pathway. Several commonly used promoters in yeast cell factories belong to glycolytic genes, highly expressed in actively growing yeast when glucose is used as a carbon source. However, their expression can be suboptimal when alternate carbon sources are used, or if there is a need to decouple growth from production. Hence, there is a need for alternate promoters for different carbon sources and production schemes. In this work, we demonstrate a reversal of regulatory function in two glycolytic yeast promoters by replacing glycolytic regulatory elements with ones induced by the diauxic shift. We observe a shift in induction from glucose-rich to glucose-poor medium without loss of regulatory activity, and strong ethanol induction. Applications of these promoters were validated for expression of the vanillin biosynthetic pathway, reaching production of vanillin comparable to pathway designs using strong constitutive promoters.

Coupling S-adenosylmethionine-dependent methylation to growth: Design and uses

We present a selection design that couples S-adenosylmethionine–dependent methylation to growth. We demonstrate its use in improving the enzyme activities of not only N-type and O-type methyltransferases by 2-fold but also an acetyltransferase of another enzyme category when linked to a methylation pathway in Escherichia coli using adaptive laboratory evolution. We also demonstrate its application for drug discovery using a catechol O-methyltransferase and its inhibitors entacapone and tolcapone. Implementation of this design in Saccharomyces cerevisiae is also demonstrated.

Many important biological processes require methylation, e.g., DNA methylation and synthesis of flavoring compounds, neurotransmitters, and antibiotics. Most methylation reactions in cells are catalyzed by S-adenosylmethionine (SAM)–dependent methyltransferases (Mtases) using SAM as a methyl donor. Thus, SAM-dependent Mtases have become an important enzyme category of biotechnological interests and as healthcare targets. However, functional implementation and engineering of SAM-dependent Mtases remains difficult and is neither cost effective nor high throughput. Here, we are able to address these challenges by establishing a synthetic biology approach, which links Mtase activity to cell growth such that higher Mtase activity ultimately leads to faster cell growth. We show that better-performing variants of the examined Mtases can be readily obtained by growth selection after repetitive cell passages. We also demonstrate the usefulness of our approach for discovery of Mtase-specific drug candidates. We further show our approach is not only applicable in bacteria, exemplified by Escherichia coli, but also in eurkaryotic organisms such as budding yeast Saccharomyces cerevisiae.

Gamma Glutamyltransferase Reduction Is Associated With Favorable Outcomes in Pediatric Primary Sclerosing Cholangitis

Adverse clinical events in primary sclerosing cholangitis (PSC) happen too slowly to capture during clinical trials. Surrogate endpoints are needed, but no such validated endpoints exist for children with PSC. We evaluated the association between gamma glutamyltransferase (GGT) reduction and long-term outcomes in pediatric PSC patients. We evaluated GGT normalization (< 50 IU/L) at 1 year among a multicenter cohort of children with PSC who did or did not receive treatment with ursodeoxycholic acid (UDCA). We compared rates of event-free survival (no portal hypertensive or biliary complications, cholangiocarcinoma, liver transplantation, or liver-related death) at 5 years. Of the 287 children, mean age of 11.4 years old, UDCA was used in 81% at a mean dose of 17 mg/kg/day. Treated and untreated groups had similar GGT at diagnosis (314 versus 300, P= not significant [NS]). The mean GGT was reduced at 1 year in both groups, with lower values seen in treated (versus untreated) patients (99 versus 175, P= 0.002), but 5-year event-free survival was similar (74% versus 77%, P= NS). In patients with GGT normalization (versus no normalization) by 1 year, regardless of UDCA treatment status, 5-year event-free survival was better (91% versus 67%, P< 0.001). Similarly, larger reduction in GGT over 1 year (> 75% versus < 25% reduction) was also associated with improved outcome (5-year event-free survival 88% versus 61%, P= 0.005). Conclusion:A GGT < 50 and/or GGT reduction of > 75% by 1 year after PSC diagnosis predicts favorable 5-year outcomes in children. GGT has promise as a potential surrogate endpoint in future clinical trials for pediatric PSC.

Design principles for nuclease-deficient CRISPR-based transcriptional regulators

The engineering of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR-associated proteins continues to expand the toolkit available for genome editing, reprogramming gene regulation, genome visualisation and epigenetic studies of living organisms. In this review, the emerging design principles on the use of nuclease-deficient CRISPR-based reprogramming of gene expression will be presented. The review will focus on the designs implemented in yeast both at the level of CRISPR proteins and guide RNA (gRNA), but will lend due credits to the seminal studies performed in other species where relevant. In addition to design principles, this review also highlights applications benefitting from the use of CRISPR-mediated transcriptional regulation and discusses the future directions to further expand the toolkit for nuclease-deficient reprogramming of genomes. As such, this review should be of general interest for experimentalists to get familiarised with the parameters underlying the power of reprogramming genomic functions by use of nuclease-deficient CRISPR technologies.

Lighting up yeast cell factories by transcription factor-based biosensors

Our ability to rewire cellular metabolism for the sustainable production of chemicals, fuels and therapeutics based on microbial cell factories has advanced rapidly during the last two decades. Especially the speed and precision by which microbial genomes can be engineered now allow for more advanced designs to be implemented and tested. However, compared to the methods developed for engineering cell factories, the methods developed for testing the performance of newly engineered cell factories in high throughput are lagging far behind, which consequently impacts the overall biomanufacturing process. For this purpose, there is a need to develop new techniques for screening and selection of best-performing cell factory designs in multiplex. Here we review the current status of the sourcing, design and engineering of biosensors derived from allosterically regulated transcription factors applied to the biotechnology work-horse budding yeast Saccharomyces cerevisiae. We conclude by providing a perspective on the most important challenges and opportunities lying ahead in order to harness the full potential of biosensor development for increasing both the throughput of cell factory development and robustness of overall bioprocesses.

An Orthogonal and pH-Tunable Sensor-Selector for Muconic Acid Biosynthesis in Yeast

Microbes offer enormous potential for production of industrially relevant chemicals and therapeutics, yet the rapid identification of high-producing microbes from large genetic libraries is a major bottleneck in modern cell factory development. Here, we develop and apply a synthetic selection system in Saccharomyces cerevisiae that couples the concentration of muconic acid, a plastic precursor, to cell fitness by using the prokaryotic transcriptional regulator BenM driving an antibiotic resistance gene. We show that the sensor-selector does not affect production nor fitness, and find that tuning pH of the cultivation medium limits the rise of nonproducing cheaters. We apply the sensor-selector to selectively enrich for best-producing variants out of a large library of muconic acid production strains, and identify an isolate that produces more than 2 g/L muconic acid in a bioreactor. We expect that this sensor-selector can aid the development of other synthetic selection systems based on allosteric transcription factors.

Engineered Production of Short-Chain Acyl-Coenzyme A Esters in Saccharomyces cerevisiae

Short-chain acyl-coenzyme A esters serve as intermediate compounds in fatty acid biosynthesis, and the production of polyketides, biopolymers and other value-added chemicals. S. cerevisiae is a model organism that has been utilized for the biosynthesis of such biologically and economically valuable compounds. However, its limited repertoire of short-chain acyl-CoAs effectively prevents its application as a production host for a plethora of natural products. Therefore, we introduced biosynthetic metabolic pathways to five different acyl-CoA esters into S. cerevisiae. Our engineered strains provide the following acyl-CoAs: propionyl-CoA, methylmalonyl-CoA, n-butyryl-CoA, isovaleryl-CoA and n-hexanoyl-CoA. We established a yeast-specific metabolite extraction protocol to determine the intracellular acyl-CoA concentrations in the engineered strains. Propionyl-CoA was produced at 4-9 μM; methylmalonyl-CoA at 0.5 μM; and isovaleryl-CoA, n-butyryl-CoA, and n-hexanoyl-CoA at 6 μM each. The acyl-CoAs produced in this study are common building blocks of secondary metabolites and will enable the engineered production of a variety of natural products in S. cerevisiae. By providing this toolbox of acyl-CoA producing strains, we have laid the foundation to explore S. cerevisiae as a heterologous production host for novel secondary metabolites.

Design, Engineering, and Characterization of Prokaryotic Ligand-Binding Transcriptional Activators as Biosensors in Yeast

In cell factory development, screening procedures, often relying on low-throughput analytical methods, are lagging far behind diversity generation methods. This renders the identification and selection of the best cell factory designs tiresome and costly, conclusively hindering the manufacturing process. In the yeast Saccharomyces cerevisiae, implementation of allosterically regulated transcription factors from prokaryotes as metabolite biosensors has proven a valuable strategy to alleviate this screening bottleneck. Here, we present a protocol to select and incorporate prokaryotic transcriptional activators as metabolite biosensors in S. cerevisiae. As an example, we outline the engineering and characterization of the LysR-type transcriptional regulator (LTTR) family member BenM from Acetinobacter sp. ADP1 for monitoring accumulation of cis,cis-muconic acid, a bioplast precursor, in yeast by means of flow cytometry.

Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR

Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. CasEMBLR capitalizes on the CRISPR/Cas9 technology to generate double-strand breaks in genomic loci, thus prompting native homologous recombination (HR) machinery to integrate exogenously derived homology templates. As proof-of-principle for microbial cell factory development, CasEMBLR was used for one-step assembly and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking out two genes. This new method complements and improves the field of genome engineering in S. cerevisiae by providing a more flexible platform for rapid and precise strain building.

System-level perturbations of cell metabolism using CRISPR/Cas9

CRISPR/Cas9 (clustered regularly interspaced palindromic repeats and the associated protein Cas9) techniques have made genome engineering and transcriptional reprogramming studies more advanced and cost-effective. For metabolic engineering purposes, the CRISPR-based tools have been applied to single and multiplex pathway modifications and transcriptional regulations. The effectiveness of these tools allows researchers to implement genome-wide perturbations, test model-guided genome editing strategies, and perform transcriptional reprogramming perturbations in a more advanced manner than previously possible. In this mini-review we highlight recent studies adopting CRISPR/Cas9 for systems-level perturbations and model-guided metabolic engineering.

Transcriptional reprogramming in yeast using dCas9 and combinatorial gRNA strategies

BACKGROUND

Transcriptional reprogramming is a fundamental process of living cells in order to adapt to environmental and endogenous cues. In order to allow flexible and timely control over gene expression without the interference of native gene expression machinery, a large number of studies have focused on developing synthetic biology tools for orthogonal control of transcription. Most recently, the nuclease-deficient Cas9 (dCas9) has emerged as a flexible tool for controlling activation and repression of target genes, by the simple RNA-guided positioning of dCas9 in the vicinity of the target gene transcription start site.

RESULTS

In this study we compared two different systems of dCas9-mediated transcriptional reprogramming, and applied them to genes controlling two biosynthetic pathways for biobased production of isoprenoids and triacylglycerols (TAGs) in baker's yeast Saccharomyces cerevisiae. By testing 101 guide-RNA (gRNA) structures on a total of 14 different yeast promoters, we identified the best-performing combinations based on reporter assays. Though a larger number of gRNA-promoter combinations do not perturb gene expression, some gRNAs support expression perturbations up to ~threefold. The best-performing gRNAs were used for single and multiplex reprogramming strategies for redirecting flux related to isoprenoid production and optimization of TAG profiles. From these studies, we identified both constitutive and inducible multiplex reprogramming strategies enabling significant changes in isoprenoid production and increases in TAG.

CONCLUSION

Taken together, we show similar performance for a constitutive and an inducible dCas9 approach, and identify multiplex gRNA designs that can significantly perturb isoprenoid production and TAG profiles in yeast without editing the genomic context of the target genes. We also identify a large number of gRNA positions in 14 native yeast target pomoters that do not affect expression, suggesting the need for further optimization of gRNA design tools and dCas9 engineering.

Engineering an NADPH/NADP+ Redox Biosensor in Yeast

Genetically encoded biosensors have emerged as powerful tools for timely and precise in vivo evaluation of cellular metabolism. In particular, biosensors that can couple intercellular cues with downstream signaling responses are currently attracting major attention within health science and biotechnology. Still, there is a need for bioprospecting and engineering of more biosensors to enable real-time monitoring of specific cellular states and controlling downstream actuation. In this study, we report the engineering and application of a transcription factor-based NADPH/NADP⁺ redox biosensor in the budding yeast Saccharomyces cerevisiae. Using the biosensor, we are able to monitor the cause of oxidative stress by chemical induction, and changes in NADPH/NADP⁺ ratios caused by genetic manipulations. Because of the regulatory potential of the biosensor, we also show that the biosensor can actuate upon NADPH deficiency by activation of NADPH regeneration. Finally, we couple the biosensor with an expression of dosage-sensitive genes (DSGs) and thereby create a novel tunable sensor-selector useful for synthetic selection of cells with higher NADPH/NADP⁺ ratios from mixed cell populations. We show that the combination of exploitation and rational engineering of native signaling components is applicable for diagnosis, regulation, and selection of cellular redox states.

Engineering of synthetic, stress-responsive yeast promoters

Advances in synthetic biology and our understanding of the rules of promoter architecture have led to the development of diverse synthetic constitutive and inducible promoters in eukaryotes and prokaryotes. However, the design of promoters inducible by specific endogenous or environmental conditions is still rarely undertaken. In this study, we engineered and characterized a set of strong, synthetic promoters for budding yeast Saccharomyces cerevisiae that are inducible under acidic conditions (pH ≤ 3). Using available expression and transcription factor binding data, literature on transcriptional regulation, and known rules of promoter architecture we improved the low-pH performance of the YGP1 promoter by modifying transcription factor binding sites in its upstream activation sequence. The engineering strategy outlined for the YGP1 promoter was subsequently applied to create a response to low pH in the unrelated CCW14 promoter. We applied our best promoter variants to low-pH fermentations, enabling ten-fold increased production of lactic acid compared to titres obtained with the commonly used, native TEF1 promoter. Our findings outline and validate a general strategy to iteratively design and engineer synthetic yeast promoters inducible to environmental conditions or stresses of interest.

EasyClone-MarkerFree: A vector toolkit for marker-less integration of genes into Saccharomyces cerevisiae via CRISPR-Cas9

Saccharomyces cerevisiae is an established industrial host for production of recombinant proteins, fuels and chemicals. To enable stable integration of multiple marker-free overexpression cassettes in the genome of S. cerevisiae, we have developed a vector toolkit EasyClone-MarkerFree. The integration of linearized expression cassettes into defined genomic loci is facilitated by CRISPR/Cas9. Cas9 is recruited to the chromosomal location by specific guide RNAs (gRNAs) expressed from a set of gRNA helper vectors. Using our genome engineering vector suite, single and triple insertions are obtained with 90-100% and 60-70% targeting efficiency, respectively. We demonstrate application of the vector toolkit by constructing a haploid laboratory strain (CEN.PK113-7D) and a diploid industrial strain (Ethanol Red) for production of 3-hydroxypropionic acid, where we tested three different acetyl-CoA supply strategies, requiring overexpression of three to six genes each. Among the tested strategies was a bacterial cytosolic pyruvate dehydrogenase complex, which was integrated into the genome in a single transformation. The publicly available EasyClone-MarkerFree vector suite allows for facile and highly standardized genome engineering, and should be of particular interest to researchers working on yeast chassis with limited markers available.

CRISPR/Cas9 advances engineering of microbial cell factories

One of the key drivers for successful metabolic engineering in microbes is the efficacy by which genomes can be edited. As such there are many methods to choose from when aiming to modify genomes, especially those of model organisms like yeast and bacteria. In recent years, clustered regularly interspaced palindromic repeats (CRISPR) and its associated proteins (Cas) have become the method of choice for precision genome engineering in many organisms due to their orthogonality, versatility and efficacy. Here we review the strategies adopted for implementation of RNA-guided CRISPR/Cas9 genome editing with special emphasis on their application for metabolic engineering of yeast and bacteria. Also, examples of how nuclease-deficient Cas9 has been applied for RNA-guided transcriptional regulation of target genes will be reviewed, as well as tools available for computer-aided design of guide-RNAs will be highlighted. Finally, this review will provide a perspective on the immediate challenges and opportunities foreseen by the use of CRISPR/Cas9 genome engineering and regulation in the context of metabolic engineering.

CasEMBLR: Cas9-Facilitated Multiloci Genomic Integration of in Vivo Assembled DNA Parts in Saccharomyces cerevisiae

Homologous recombination (HR) in Saccharomyces cerevisiae has been harnessed for both plasmid construction and chromosomal integration of foreign DNA. Still, native HR machinery is not efficient enough for complex and marker-free genome engineering required for modern metabolic engineering. Here, we present a method for marker-free multiloci integration of in vivo assembled DNA parts. By the use of CRISPR/Cas9-mediated one-step double-strand breaks at single, double and triple integration sites we report the successful in vivo assembly and chromosomal integration of DNA parts. We call our method CasEMBLR and validate its applicability for genome engineering and cell factory development in two ways: (i) introduction of the carotenoid pathway from 15 DNA parts into three targeted loci, and (ii) creation of a tyrosine production strain using ten parts into two loci, simultaneously knocking out two genes. This method complements and improves the current set of tools available for genome engineering in S. cerevisiae.

Cost-effectiveness analysis of treatment strategies for initial Clostridium difficile infection

Clostridium difficile infection (CDI) is costly. Current guidelines recommend metronidazole as first-line therapy and vancomycin as an alternative. Recurrence is common. Faecal microbiota transplantation (FMT) is an effective therapy for recurrent CDI (RCDI). This study explores the cost-effectiveness of FMT, vancomycin and metronidazole for initial CDI. We constructed a decision-analytic computer simulation using inputs from published literature to compare FMT with a 10-14-day course of oral metronidazole or vancomycin for initial CDI. Parameters included cure rates (baseline value (range)) for metronidazole (80% (65-85%)), vancomycin (90% (88-92%)) and FMT(91% (83-100%)). Direct costs of metronidazole, vancomycin and FMT, adjusted to 2011 dollars, were $57 ($43-72), $1347 ($1195-1499) and $1086 ($815-1358), respectively. Our effectiveness measure was quality-adjusted life years (QALYs). One-way and probabilistic sensitivity analyses were conducted from the third-party payer perspective. Analysis using baseline values showed that FMT($1669, 0.242 QALYs) dominated (i.e. was less costly and more effective) vancomycin ($1890, 0.241 QALYs). FMT was more costly and more effective than metronidazole ($1167, 0.238 QALYs), yielding an incremental cost-effectiveness ratio (ICER) of $124 964/QALY. One-way sensitivity analyses showed that metronidazole dominated both strategies if its probability of cure were >90%; FMT dominated if it cost <$584. In a probabilistic sensitivity analysis at a willingness-to-pay threshold of $100 000/QALY, metronidazole was favoured in 55% of model iterations; FMT was favoured in 38%. Metronidazole, as the first-line treatment for CDIs, is less costly. FMT and vancomycin are more effective. However, FMT is less likely to be economically favourable, and vancomycin is unlikely to be favourable as first-line therapy when compared with FMT.

Multiplex metabolic pathway engineering using CRISPR/Cas9 in Saccharomyces cerevisiae

CRISPR/Cas9 is a simple and efficient tool for targeted and marker-free genome engineering. Here, we report the development and successful application of a multiplex CRISPR/Cas9 system for genome engineering of up to 5 different genomic loci in one transformation step in baker's yeast Saccharomyces cerevisiae. To assess the specificity of the tool we employed genome re-sequencing to screen for off-target sites in all single knock-out strains targeted by different gRNAs. This extensive analysis identified no more genome variants in CRISPR/Cas9 engineered strains compared to wild-type reference strains. We applied our genome engineering tool for an exploratory analysis of all possible single, double, triple, quadruple and quintuple gene disruption combinations to search for strains with high mevalonate production, a key intermediate for the industrially important isoprenoid biosynthesis pathway. Even though we did not overexpress any genes in the mevalonate pathway, this analysis identified strains with mevalonate titers greater than 41-fold compared to the wild-type strain. Our findings illustrate the applicability of this highly specific and efficient multiplex genome engineering approach to accelerate functional genomics and metabolic engineering efforts.

Recent applications of synthetic biology tools for yeast metabolic engineering

The last 20 years of metabolic engineering has enabled bio-based production of fuels and chemicals from renewable carbon sources using cost-effective bioprocesses. Much of this work has been accomplished using engineered microorganisms that act as chemical factories. Although the time required to engineer microbial chemical factories has steadily decreased, improvement is still needed. Through the development of synthetic biology tools for key microbial hosts, it should be possible to further decrease the development times and improve the reliability of the resulting microorganism. Together with continuous decreases in price and improvements in DNA synthesis, assembly and sequencing, synthetic biology tools will rationalize time-consuming strain engineering, improve control of metabolic fluxes, and diversify screening assays for cellular metabolism. This review outlines some recently developed synthetic biology tools and their application to improve production of chemicals and fuels in yeast. Finally, we provide a perspective for the challenges that lie ahead.